1. Field of the Invention
The present invention relates to an image signal coding method and device thereof, an image signal decoding method and device thereof, and a recording medium being recorded with a recording signal capable of being decoded by an image decoding device, and more particularly relates to an image signal coding method and device thereof, an image signal decoding method and device thereof, and a recording medium capable of being widely applied to the recording of digitized moving image sequences or digitized still images onto a recording medium such as, for example, video tape, video disc or semiconductor memory etc. or capable of being widely applied to television broadcasts, television conferencing systems or communication networks.
2. Description of Related Art
In recent years, a great deal of progress has been made in research into efficient transmission and recording of digital audio, digital images and video sequences. This technology can be applied to, for example, digital video recording, videophones, interactive television and interactive games, etc. However, data compression is necessary in order to reduce the amount of data transmitted because a large amount of data is included in the image signal. Of this kind of technological research, the widely known Moving Pictures Experts Group (MPEG) technology has become standard in cooperation with the International Organization of Standardization (ISO) and the International Electrotechincal Commission (IEC). Here, an MPEG method exists that is a hybrid method that is a combination of motion compensation estimation coding and discrete cosine transforms (DCT).
Further, other coding methods such as sub-band transform coding and wavelet transform coding etc. are generally well known. These transform coding methods are generally used to compress images because image energy compression is good, as is texture region performance.
That relating to sub-band transforms is described in, for example, the reference, "J. Wood, Sub-band image coding, Kluwer Academic Publishers, Boston Mass. 1991".
Further, that relating to wavelet transforms is described in, for example, the reference, "I. Daubechies, Orthonormal bases of compactly supported wavelets, Commun. Pure Appl. Math. vol. 41. pp. 961 to 966, 1988".
In particular, with wavelet transforms it is possible to focus most of the energy of the image into a small portion of the sample while maintaining all of the energy. The uneven distribution of the energy of the transformed image is then utilized in the compression algorithm. The basic way of considering these sub-band wavelet transforms is that, for example, as shown in FIG. 2, the signal band is divided into a plurality of sub-bands and a large portion of the total energy of the image is concentrated into one frequency band (lower most frequency component band). For example, FIGS. 3A and 3B show a transform coefficient obtained from a three-layer sub-band/wavelet transform for a typical image. Layer #0 (lower most layer), layer #1, and layer #2 (upper most layer) correspond to frequency groups and as shown in FIGS. 3A and 3B, the coefficients of each group are gathered together in accordance with their spatial position. These sub-band/wavelet transform coefficients that are gathered together are first quantized. The quantized coefficients are then compressed using coding methods of a high compression efficiency such as Hoffman Coding, Variable Length Coding (VLC) or Arithmetic Coding, as are described in the following reference paper.
For example, that related to Huffman Coding such as that in, for example, "D. Huffman, A method for construction of minimum redundancy codes. Proceedings of the Institute of Radio Engineers, pp. 1098 to 1101, September 1952".
Further, that related to Arithmetic Coding technology such as that in, for example, "G. Langdon and J. Rissanen. A simple general binary source code, IEEET, Transactions on Information Theory, vol. IT-28(5), pp. 800 to 803, September 1982".
It is extremely important to gather together quantization coefficients in order to compress efficiently with little loss. A technology for an efficient data structure for gathering together quantization coefficients in order to code with little loss is one where coefficients are gathered together in different layers using a tree structure, with this tree structure being referred to here as a coefficient tree structure.
The relating to tree structures is described in, for example, the reference, "J. Shapiro. Embedded image coding using zero trees of wavelet coefficients. IEER transactions on Signal Processing. vol. 41. no. 12, pp. 3445 to 4361, December 1993", and
"A. Lewis and G. Knowles. Image compression using the 2-D wavelet transform, IEEE Transactions on Image Processing. vol. 1, no. 2. pp. 244 to 250, April 1992".
With a sub-band coded hierarchical structure, coefficients belonging to the uppermost layer are removed and each coefficient of a certain layer has a relationship with the coefficient existing one layer down in the same direction and spatial position. FIGS. 3A and 3B are views showing a coefficient tree data structure comprising different layers of coefficients. In the method of J. Shapiro, the same wavebands of different wavelet transforms i.e. all of the coefficients at spatially the same positions within different layers that are the sub-trees present in the un-valued coefficients are referred to as zero sub-trees. The expressing and coding of coefficient trees (i.e. zero trees) where all of the coefficients are un-valued coefficients can be achieved with only one symbol. In other words, a zero tree can be sufficiently coded with few bits. However, when valued coefficients are distributed between different layers of coefficient trees, zero tree coding is not efficient. Zero tree coding is therefore not effective when coding valued coefficients. In this case, all of the symbols including zero have to be coded in zero tree coding.
Further, with zero tree coding, only one sub-tree can be coded at a time even in cases where all of the coefficients of neighboring coefficient trees have a high correlation.
On the other hand, a run length coding method can also be considered as a further method for coding coefficient trees. The is a typical effective method for coding consecutive symbol strings that are the same. However, it is no longer necessary to code these symbols one at a time as un-valued coefficients of quantized sub-band/wavelet transform coefficients are considered to be the same consecutive symbol. Therefore, in low bit rate coding where the likelihood of a quantization coefficient being an un-valued coefficient is very high in particular it is possible to have efficient coding. Further, when there is a high degree of correlation between neighboring trees, a plurality of trees can be encoded at one time by scanning across the trees. However, when run length coding is carried out so as to include the lowermost frequency band, the number of kinds of run length increases and the overhead due to the run length coding can increase even after changing.
As it is the object of the present invention to resolve the situation encountered in the aforementioned related image signal coding method and device thereof, it is the object of the present invention to provide an image signal coding method and device thereof, an image signal decoding method and device thereof, and a recording medium capable of coding, for example, wavelet transform coefficients occurring in sub-band coding in a more efficient manner than related methods and devices.